Abstract: With the continual increase of urban traffic demand, traffic congestion occurs more and more frequently.Ramp metering, by regulating the vehicles entering freeway, has been proved to be an effective measure of relieving freeway congestion.This paper presents an optimal ramp metering algorithm with full consideration of the dynamic freeway and ramp density.The algorithm aims to maintain freeway density near the critical value and minimize the ramp queues.The PARAMICS is used to evaluate its performance comparing with the ALINEA and DemandCapacity algorithms.The data of freeway density, ramp queues, total vehicle travel time and downstream flow are also collected for each simulation.Analysis result shows that the Densitybased algorithm is effective in maximizing mainline traffic flow, optimizing the balance of network traffic condition and reducing ramp queues.

Key words: intelligent transportation systems (ITS), onramp metering control, realtime density measurement, Quadstone Paramics, inputoutput vehicle counting method

摘要： 随着城市汽车保有量的不断增加，交通拥堵日益频繁；匝道控制是通过调节入口匝道车辆数，来缓解快速路匝道交汇处拥堵的有效方法.本文同时考虑快速路和入口匝道上的实时密度设计了匝道控制优化算法，该算法旨在控制快速路密度接近其最优值，同时减少匝道上的排队数；通过PARAMICS仿真软件对算法进行验证，并与ALINEA、DemandCapacity算法进行了比较，仿真模拟统计了快速路交通流密度、匝道排队数、总车辆行程时间以及下游流量数据.分析结果显示，实时密度控制算法是有效的，能够维持干线最大流量，保持路网交通条件的动态平衡，并且尽可能地减少排队长度.

关键词: 智能交通系统, 入口匝道控制, 实时密度测量, Quadstone Paramics, 进出计数法